Triple
T2351186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Macbeth |
E47451
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Dan Jones |
E155532
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Dan Jones | Statement: [Lady Macbeth, musicBy, Dan Jones]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Jones Context triple: [Lady Macbeth, musicBy, Dan Jones]
-
A.
Dan Jones
chosen
Dan Jones is a British composer and sound designer known for his award-winning scores for film, television, and theatre.
-
B.
Alexander Jones
Alexander Jones was a Catholic biblical scholar and priest best known for overseeing and editing the English translation of the Jerusalem Bible in the 1960s.
-
C.
Mark Jones
Mark Jones was an English footballer for Manchester United and England who died in the 1958 Munich air disaster.
-
D.
John Seale
John Seale is an Australian cinematographer renowned for his Academy Award–winning work on films such as "The English Patient" and his visually striking collaborations with major directors.
-
E.
Jeremy Black
Jeremy Black is a British historian renowned for his prolific scholarship on military history, international relations, and the history of warfare.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc6f75d888190a2e41edaa532e83f |
completed | March 7, 2026, 6:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae962f769881909a7713880eaa9b84 |
completed | March 9, 2026, 9:43 a.m. |
Created at: March 4, 2026, 7:54 p.m.